EDCO 745 Data Screening Assignment

Data screening is fundamental before any analysis. The basics of data screening are outlined in your Warner text. Data screening is used for two major purposes: removing bad cases (missing responses or nonresponse patterns) and testing the assumptions (distribution of quantitative variables, sample size requirements for analysis, removal of small groups) of the intended analysis. This is one of three data screening assignments you will have in this class. This assignment is a general data screening exercise intended to prepare you for the remaining of the rest of the term.

Instructions

• After opening the SPSS file (click on it, it will open)

• Note: there are variable view and data view

Graphical user interface, application Description automatically generated

1. Choose:

• 2 categorical variables ( often represent naturally occurring groups or categories – i.e. gender)

AND

• 2 quantitative variables ( provide information about the magnitude of differences between participants, in terms of the amount of some characteristics – i.e. anxiety)

*For further questions regarding categorical versus quantitative variables, see Applied Statistics I, pp. 31-33

2. Go through the data screening process outlined in Applied Statistics I & II.

· Frequency Tables – Applied Statistics I, pp. 37-50

· Histograms- Applied Statistics I, pp. 103-115

· Boxplots- Applied Statistics I, pp. 115-120

· Bar graphs – Applied Statistics I, pp. 100-103

· Scatterplots- Applied Statistics I, pp. 126-127

Write a data screening story consistent with Warner’s instructions (- Applied Statistics I, pp. 37-50).

• Make sure you include both your output:

It should have:

1. Frequency Tables for all four variables

2. Histograms (2): One for each quantitative variable.

3. Bar Graph (2): One for categorical variable

4. Boxplots (4): Two Graphs for each Category (e.g., gender X anxiety and gender x depression)

5. Scatterplot (1): Quant x Quant

Note: Your assignment will be checked for originality via the Turnitin plagiarism tool.

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